Implementing WFM Historical Schedule Migration from Verint to Genesys Cloud WFM
What This Guide Covers
You are migrating your Workforce Management (WFM) operations from Verint Impact 360 to Genesys Cloud WFM. A critical part of this transition is migrating historical schedule data. This is necessary for calculating “Schedule Adherence” for previous months and for providing the Genesys Cloud AI forecasting engine with the historical “Actual Work” data it needs to generate accurate future schedules. This guide covers the data extraction patterns from Verint and the programmatic ingestion into Genesys Cloud via the WFM APIs.
Prerequisites, Roles & Licensing
- Genesys Cloud: CX 3 (WFM is included) or CX 1/2 with WFM Add-on.
- Verint: Access to the Verint SQL Database (Impact 360) or the Verint Data Extract API.
- Tooling: Python with
pandasandrequests. - Permissions:
Workforcemanagement > Schedule > ImportWorkforcemanagement > ManagementUnit > View
The Implementation Deep-Dive
1. Extracting Data from Verint
Verint stores schedule data in a complex relational schema. You need to extract the “Published Schedule” for each agent, including Activity codes (Work, Break, Lunch, Training).
Verint SQL Extraction Pattern:
SELECT
EmployeeID,
StartTime,
EndTime,
ActivityName,
TimeZone
FROM Verint_Schedules
WHERE StartTime BETWEEN '2026-01-01' AND '2026-03-31'
2. Normalizing Activity Codes
Map your Verint Activity IDs to Genesys Cloud Activity Codes.
| Verint Activity | Genesys Cloud Activity |
|---|---|
Phone - Inbound |
On Queue |
Meal |
Break |
Coaching |
Meeting |
Time Off |
Time Off |
3. Preparing the JSON Ingestion Payload
Genesys Cloud WFM uses a specific JSON structure for importing schedules. Each agent’s schedule is a list of “shifts” and “activities.”
{
"managementUnitId": "your-mu-id",
"agentSchedules": [
{
"userId": "agent-uuid-in-genesys",
"shifts": [
{
"startDate": "2026-05-15T08:00:00Z",
"lengthMinutes": 480,
"activities": [
{ "activityCodeId": "work-code-id", "startOffsetMinutes": 0, "lengthMinutes": 240 },
{ "activityCodeId": "break-code-id", "startOffsetMinutes": 240, "lengthMinutes": 30 }
]
}
]
}
]
}
4. Mapping User IDs
You must map Verint EmployeeIDs to Genesys Cloud UserIDs.
Mapping Strategy:
- Use the Email Address as the common key.
- Fetch all Genesys users via
/api/v2/usersand build a lookup table:{ "email@company.com": "genesys-uuid" }.
5. Executing the Import (Python)
Use the POST /api/v2/workforcemanagement/managementunits/{muId}/schedules/import endpoint.
import requests
def import_historical_schedule(token, mu_id, payload):
headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
url = f"https://api.mypurecloud.com/api/v2/workforcemanagement/managementunits/{mu_id}/schedules/import"
resp = requests.post(url, headers=headers, json=payload)
if resp.status_code == 202:
print("Import job started successfully.")
else:
print(f"Error: {resp.text}")
Validation, Edge Cases & Troubleshooting
Edge Case 1: Time Zone Offsets
Verint data may be stored in local server time, while Genesys Cloud API expects ISO-8601 UTC.
Solution: Always convert timestamps to UTC during the extraction/normalization phase to avoid 1-hour shifts during Daylight Savings transitions.
Edge Case 2: Incompatible Activity Overlaps
Verint might allow overlapping activities (e.g., a “Meeting” scheduled during a “Shift”). Genesys Cloud WFM is stricter.
Solution: Implement a validation script that “flattens” the schedule before import. Ensure only one activity exists for any given minute per agent.
Edge Case 3: Management Unit (MU) Mismatches
If an agent was in “Team A” in Verint but is in “Team B” in Genesys, the import might fail or put data in the wrong bucket.
Solution: Ensure the managementUnitId in your payload matches the current MU assignment of the user in Genesys Cloud.